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HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores. <i>IEEE Transactions on Power Electronics</i>. 2025;40(2):3326-3335. doi:<a href=\"https://doi.org/10.1109/TPEL.2024.3488174\">10.1109/TPEL.2024.3488174</a>","ieee":"W. Kirchgässner, N. Förster, T. Piepenbrock, O. Schweins, and O. Wallscheid, “HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores,” <i>IEEE Transactions on Power Electronics</i>, vol. 40, no. 2, pp. 3326–3335, 2025, doi: <a href=\"https://doi.org/10.1109/TPEL.2024.3488174\">10.1109/TPEL.2024.3488174</a>.","chicago":"Kirchgässner, Wilhelm, Nikolas Förster, Till Piepenbrock, Oliver Schweins, and Oliver Wallscheid. “HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores.” <i>IEEE Transactions on Power Electronics</i> 40, no. 2 (2025): 3326–35. <a href=\"https://doi.org/10.1109/TPEL.2024.3488174\">https://doi.org/10.1109/TPEL.2024.3488174</a>.","short":"W. Kirchgässner, N. Förster, T. Piepenbrock, O. Schweins, O. Wallscheid, IEEE Transactions on Power Electronics 40 (2025) 3326–3335.","mla":"Kirchgässner, Wilhelm, et al. “HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores.” <i>IEEE Transactions on Power Electronics</i>, vol. 40, no. 2, 2025, pp. 3326–35, doi:<a href=\"https://doi.org/10.1109/TPEL.2024.3488174\">10.1109/TPEL.2024.3488174</a>.","bibtex":"@article{Kirchgässner_Förster_Piepenbrock_Schweins_Wallscheid_2025, title={HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores}, volume={40}, DOI={<a href=\"https://doi.org/10.1109/TPEL.2024.3488174\">10.1109/TPEL.2024.3488174</a>}, number={2}, journal={IEEE Transactions on Power Electronics}, author={Kirchgässner, Wilhelm and Förster, Nikolas and Piepenbrock, Till and Schweins, Oliver and Wallscheid, Oliver}, year={2025}, pages={3326–3335} }","apa":"Kirchgässner, W., Förster, N., Piepenbrock, T., Schweins, O., &#38; Wallscheid, O. (2025). HARDCORE: H-Field and Power Loss Estimation for Arbitrary Waveforms With Residual, Dilated Convolutional Neural Networks in Ferrite Cores. <i>IEEE Transactions on Power Electronics</i>, <i>40</i>(2), 3326–3335. <a href=\"https://doi.org/10.1109/TPEL.2024.3488174\">https://doi.org/10.1109/TPEL.2024.3488174</a>"},"intvolume":"        40","page":"3326-3335","year":"2025","user_id":"83383","department":[{"_id":"52"}],"_id":"63498","keyword":["Mathematical models","Estimation","Data models","Convolutional neural networks","Accuracy","Magnetic hysteresis","Magnetic cores","Temperature measurement","Magnetic domains","Temperature distribution","Convolutional neural network (CNN)","machine learning (ML)","magnetics"],"type":"journal_article","publication":"IEEE Transactions on Power Electronics","status":"public"},{"article_number":"100174","user_id":"94996","department":[{"_id":"43"}],"_id":"46637","status":"public","type":"journal_article","main_file_link":[{"open_access":"1","url":"https://www.sciencedirect.com/science/article/pii/S2666352X23000638"}],"doi":"10.1016/j.jaecs.2023.100174","author":[{"first_name":"Munko","orcid":"https://orcid.org/0000-0002-7773-047X","last_name":"Gonchikzhapov","full_name":"Gonchikzhapov, Munko","id":"94996"},{"id":"94562","full_name":"Kasper, Tina","last_name":"Kasper","orcid":"0000-0003-3993-5316 ","first_name":"Tina"}],"volume":15,"date_updated":"2023-08-24T08:55:26Z","oa":"1","citation":{"apa":"Gonchikzhapov, M., &#38; Kasper, T. (2023). Thermal and chemical structure of ethanol and 2-ethylhexanoic acid/ethanol SpraySyn flames. <i>Applications in Energy and Combustion Science</i>, <i>15</i>, Article 100174. <a href=\"https://doi.org/10.1016/j.jaecs.2023.100174\">https://doi.org/10.1016/j.jaecs.2023.100174</a>","mla":"Gonchikzhapov, Munko, and Tina Kasper. “Thermal and Chemical Structure of Ethanol and 2-Ethylhexanoic Acid/Ethanol SpraySyn Flames.” <i>Applications in Energy and Combustion Science</i>, vol. 15, 100174, Elsevier BV, 2023, doi:<a href=\"https://doi.org/10.1016/j.jaecs.2023.100174\">10.1016/j.jaecs.2023.100174</a>.","short":"M. Gonchikzhapov, T. 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Kasper, “Thermal and chemical structure of ethanol and 2-ethylhexanoic acid/ethanol SpraySyn flames,” <i>Applications in Energy and Combustion Science</i>, vol. 15, Art. no. 100174, 2023, doi: <a href=\"https://doi.org/10.1016/j.jaecs.2023.100174\">10.1016/j.jaecs.2023.100174</a>.","ama":"Gonchikzhapov M, Kasper T. Thermal and chemical structure of ethanol and 2-ethylhexanoic acid/ethanol SpraySyn flames. <i>Applications in Energy and Combustion Science</i>. 2023;15. doi:<a href=\"https://doi.org/10.1016/j.jaecs.2023.100174\">10.1016/j.jaecs.2023.100174</a>"},"intvolume":"        15","publication_status":"published","publication_identifier":{"issn":["2666-352X"]},"language":[{"iso":"eng"}],"keyword":["Nanoparticle synthesis","Flame spray pyrolysis","SpraySyn burner","Flame structure","Species distribution","Temperature distribution"],"publication":"Applications in Energy and Combustion Science","title":"Thermal and chemical structure of ethanol and 2-ethylhexanoic acid/ethanol SpraySyn flames","date_created":"2023-08-22T13:26:37Z","publisher":"Elsevier BV","year":"2023"}]
